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All Journal Teknosains: Media Informasi Sains dan Teknologi Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal INSYPRO (Information System and Processing) JURNAL INSTEK (Informatika Sains dan Teknologi) Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya EIGEN MATHEMATICS JOURNAL Jurnal Sehat Mandiri Bulletin of Economic Studies (BEST) JES-MAT (Jurnal Edukasi dan Sains Matematika) Parameter: Jurnal Matematika, Statistika dan Terapannya Journal of Mathematics, Computation and Statistics (JMATHCOS)
Adnan Sauddin
Univeristas Islam Negeri Alauddin Makassar
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Mathematics Medicine & Pharmacology Physics Public Health Other

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Logistik Regression Analysis of Factor Influencing Drung Abuse Cases for Inmates in Class IIA Parepare Prison Ale Miftahulhaer, Ale Miftahulhaer; Wahidah Alwi; Adnan Sauddin; Khalilah Nurfadilah
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9448

Abstract

Drugs are addictive substances that can have a negative impact on the body, especially on the central nervous system. Drug abuse can be caused by various factors including parental influence, knowledge, attitudes, family structure, peer pressure, and community environment. The purpose of this study was to identify the factors asociated with drug abuse cases in Class IIA Parepare Prison. The sample consisted of 85 respondebts from cases related to drug abuse in the prison. Logistic regression analysis was ued, with drug abuse status (using drugs/not using drugs) as the dependent variable and gender, age, knowledge, family, peers, and community environment as independent variables. The results of this study indicate that a high level of knowledge has a regression odds ratio of 13.6489. This indicate that inmates with higher knowledge about drugs had a significantly greater likelihood of avoiding drug abuse compared to those with lower knowledge.
Analilis Pendekatan Metode Vector Autoregressive (VAR) dalam Meramalkan Jumlah Pengadaan Beras di Sulawesi Selatan Yulia, Yulia Novita Sari; Adnan Sauddin; Khalilah Nurfadilah
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 12 No 2 (2024): VOLUME 12 NO 2 TAHUN 2024
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v12i2.32340

Abstract

This study discusses forecasting the amount of rice procurement in South Sulawesi. The need increases every year because it is one of the staple foods of the Indonesian population that is consumed everyday. Related to this, to ensure the availability of stock of rice suppiles throughout the South Sulawesi region, this is done by estimating the number of procurements in terms of rice prices and rice production. The purpose of this study is to determine the forecasting model, the variables that have a relationship between variables and the results of forecasting the amount of rice procurement. The results obtained in this study indicate that the smallest AIC value is found in the length of lag 2 so that the model used is the VAR model (3). In addition, all the variables used have a significant effect. Then from the forecasting results obtained, the rice price variabes (Y1) and the amount of rice production (Y2) have MAPE values of 20,4 % dan 14,0 %, which means the forecasting results are good. The results of the forecast number of procurement based on the price in term of the price of rice and the amount of production in the text five years has increased every year.
Peramalan Jumlah Penumpang Kapal Laut Menggunakan Metode Time Series Machine Learning di PT Pelabuhan Indonesia (Persero) Ragional 4 (Studi Kasus Pada Pelabuhan Soekarno Hatta Makassar) Rismawati; Alwi, Wahidah; Sauddin, Adnan; Adiatma
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 12 No 2 (2024): VOLUME 12 NO 2 TAHUN 2024
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v12i2.51076

Abstract

ABSTRAK, Penelitian ini membahas tentang Peramalan Jumlah Penumpang Pelabuhan Soekarno Hatta Makassar pada PT Pelabuhan Indonesia (Persero) Ragional 4. Jumlah penumpang Pelabuhan Soekarno Hatta Makassar sering mengalami lonjakan jumlah penumpang ketika musim libur, hari raya maupun akhir tahun. Metode yang digunakan dalam menyelesaikan masalah peramalan jumlah penumpang yaitu menggunakan Long Short Term Memory. Penelitian ini bertujuan untuk mengetahui model Long Short Term Memory yang kemudian digunakan untuk meramalkan jumlah penumpang keberangkatan pada kapal PELNI, serta mengetahui tingkat akurasi hasil prediksi menggunakan metode Long Short Term Memory. Berdasarkan hasil penelitian model LSTM yang diperoleh yaitu model sequential 3 layer terdiri dari dua layer LSTM dan satu layer dense dengan jumlah neuron hidden layer yaitu 10, jumlah batch size yaitu 1 dan jumlah epoch yaitu 100, serta menggunakan optimasi Adam dengan learning rate 0,01 di dapatkan Hasil peramalan dari Januari 2023 sebanyak 33.143 penumpang hingga Desember 2023 sebanyak 25.151 penumpang. Tingkat akurasi nilai MAPE yaitu sebesar %. Berdasarkan aturan range nilai MAPE yang didapatkan, dapat dikatakan bahwa akurasi peramalan yang dilakukan termasuk kedalam kategori baik karena nilai MAPE 10-20%.
Autoregressive Distributed Lag (ARDL) Method for Estimating Poverty Levels in Polewali Mandar Regency Abeng, Andi Tenri; Alwi, Wahidah; Sauddin, Adnan; Anugrawati, Sri Dewi; Aeni, Nur
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.60197

Abstract

Polewali Mandar Regency is the region with the highest poverty rate in West Sulawesi. According to a publication by the Central Bureau of Statistics in March 2022, the percentage of the poor population was 11.75%, an increase compared to March 2021. The forecasting method used in this study is the Autoregressive Distributed Lag (ARDL) method. This study aims to determine the Autoregressive Distributed Lag (ARDL) model, which is then used to forecast the number of poor people in Polewali Mandar Regency. The results of the study using the ARDL method yielded the best estimation model, namely ARDL (3, 3, 2, 2). The forecast results for the percentage of the poor population using the ARDL (3, 3, 2, 2) model for the following semesters are 21.79%, 10.15%, and 16.52%, respectively. The forecasting accuracy test using the Mean Absolute Percentage Error (MAPE) yielded a value of 12.18%, indicating that the ARDL model produced in this study is suitable for forecasting the percentage of the poor population in Polewali Mandar Regency.
Comparison of Random Forest and XGBoost Methods for Predicting Work Accident Claim Reserves Anugrah, Sri Ayu; Anugrawati, Sri Dewi; Sauddin, Adnan; Mariani, Andi
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp497-508

Abstract

The potential high claim burden in the work accident insurance sector managed by BPJS Ketenagakerjaan have an impact on the company’s financial stability. This encourages insurance companies to provide additional funds to maintain the company’s operational sustainability. Thus, preparing future fund reserves is a crucial step in risk and financial management to minimize payment delays, up to the risk of default. This study aims to determine the best method for predicting work accident claim reserves by comparing the Random Forest and XGBoost methods. The result of the analysis shows that the XGBoost method has an outstanding ability to predict work accident claim reserves on BPJS Ketenagakerjaan in the period July 2016 to August 2023, with a MAPE of 5.14% and an accuracy rate of 94.86%.
Co-Authors A. Hikmawati Abeng, Andi Tenri Adiatma Adiatma Adiatma Adiatma Adiatma Ale Miftahulhaer, Ale Miftahulhaer Amma, Karmatang AN, Ningsih Andi Mariani Andi Mariani Anita Kaimuddin Anugrah, Sri Ayu Anugrawati, Sri Dewi Asfar Asmarianti Astuti - Auliah, Nur Indah Bakri, Nurjannah Ermawati Faradila, Adhe Hayati Hayati Herianto Ilham Nur Ilahi Ilma Islamiyah, Nurul Irwan Irwan Irwan Irwan Kasse Iswanto, Ardi Kumaladewi, Yanti M. Ikhsan Amarta Muh Irwan Muh. Irzan Muhalki Muhalki Muhammad Muhadir Aludin Muhammad Ridwan Munawwarah Nahda Islamiah. M Nawawi, M. Ichsan Nawawi, Moh. Ichsan Nirmala Nirmala, Nirmala Nirwana Nufus, Husnatun Nur Aeni Nur Aeni Nur Ida Nurfadilah, Khalilah Nurliani Nurliani Nurma, Try Azisah Nurul Inayah NURUL WULANDARI Oktaviani, Risqi Ramadhani, Nur Suci Rasyid, Adiatma Ratnasari Reni Astuti Riqas, Ahmad Rismawati Risnawati Ibnas Rizaldy, Adhy Sadem Rahayu Sudarta Salim, Muhammad Ihsan Sumarni, Kiki Upe, Indo Vivi Feromida Wahidah Alwi Wahidah Alwi Wahyuni Abidin Wahyuni, Risa Winda Saputri WS Athiyyah Hazimah Yulia, Yulia Novita Sari Z, Eldasari